← AI reinforcement-learning environments
What podcasts say about AI reinforcement-learning environments
Every statement, with the speaker, the exact quote and the moment it was said.
What experts have said about AI reinforcement-learning environments
2 statements · 1 mixed · 1 neutral
A ladder of RL environments could reach human-level AI research, but each successive rung requires exponentially more effort.
“there's probably a ladder of RL environments that is possible to construct such that you would get an AI researcher which is at least as good as a human researcher, but the effort to climb each successive rung grows exponentially”
Open the episode · AI researchers debate how close we are to recursive self-improvementListen at 1:01:15
Better RL environments mainly reflect improved design knowledge and AI labor, not more human experts.
“The reason why RL environments today are much better than they were in 2024 is not that much because we have hired way more human experts to make RL environments. It is instead much more, because we better know what RL environments we even want to make and how we should structure them. And also we're using huge amounts of AI labor to build RL environments.”
Open the episode · Ryan Greenblatt – Human level AIs might build runaway superintelligences by 2032Listen at 21:18
Statements are attributed to the speaker as said on the episode and reflect their view at the time, not PodLume's. They are not advice.